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Reduced-order constrained optimization in IMRT planning

Renzhi Lu1, Richard J Radke1, Jie Yang2, Laura Happersett2, Ellen Yorke2 and Andrew Jackson2

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This paper presents a new algorithm for constrained intensity-modulated radiotherapy (IMRT) planning, made tractable by a dimensionality reduction using a set of plans obtained by fast, unconstrained optimizations. The main result is to reduce planning time by an order of magnitude, producing viable five field prostate IMRT plans in about 5 min. Broadly, the algorithm has three steps. First, we solve a series of independent unconstrained minimization problems based on standard penalty-based objective functions, 'probing' the space of reasonable beamlet intensities. Next, we apply principal component analysis (PCA) to this set of plans, revealing that the high-dimensional intensity space can be spanned by only a few basis vectors. Finally, we parameterize an IMRT plan as a linear combination of these few basis vectors, enabling the fast solution of a constrained optimization problem for the desired intensities. We describe a simple iterative process for handling the dose–volume constraints that are typically required for clinical evaluation, and demonstrate that the resulting plans meet all clinical constraints based on an approximate dose calculation algorithm.


PACS

87.55.-x Treatment strategy

02.50.-r Probability theory, stochastic processes, and statistics

Subjects

Computational physics

Dates

Issue 23 (7 December 2008)

Received 14 July 2008, in final form 29 September 2008

Published 7 November 2008



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